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  # Bark
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- This is the official codebase for running the text to audio model, from [Suno.ai](www.suno.ai).
 
 
 
 
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- The original github repo and model card can be found [here](https://github.com/suno-ai/bark)
 
 
 
 
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  The following is additional information about the models released here.
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  ### Architecture
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  | Model | Parameters | Attention | Output Vocab size |
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  |:-------------------------:|:----------:|------------|:-----------------:|
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- | Text to semantic tokens | 80 M | Causal | 10,000 |
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- | Semantic to coarse tokens | 80 M | Causal | 2x 1,024 |
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- | Coarse to fine tokens | 80 M | Non-causal | 6x 1,024 |
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  ### Release date
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  ## Broader Implications
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  We anticipate that this model's text to audio capabilities can be used to improve accessbility tools in a variety of languages.
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- Straightforward improvements will allow models to run faster than realtime, rendering them useful for applications such as virtual assistants.
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  While we hope that this release will enable users to express their creativity and build applications that are a force
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  for good, we acknowledge that any text to audio model has the potential for dual use. While it is not straightforward
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- to voice clone known people with Bark, they can still be used for nefarious purposes. To further reduce the chances of unintended use of Bark,
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  we also release a simple classifier to detect Bark-generated audio with high accuracy (see notebooks section of the main repository).
 
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  # Bark
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+ Bark is a transformer-based text-to-audio model created by [Suno](https://www.suno.ai).
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+ Bark can generate highly realistic, multilingual speech as well as other audio - including music,
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+ background noise and simple sound effects. The model can also produce nonverbal
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+ communications like laughing, sighing and crying. To support the research community,
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+ we are providing access to pretrained model checkpoints ready for inference.
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+ The original github repo and model card can be found [here](https://github.com/suno-ai/bark).
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+
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+ This model is meant for research purposes only.
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+ The model output is not censored and the authors do not endorse the opinions in the generated content.
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+ Use at your own risk.
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  The following is additional information about the models released here.
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  ### Architecture
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  | Model | Parameters | Attention | Output Vocab size |
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  |:-------------------------:|:----------:|------------|:-----------------:|
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+ | Text to semantic tokens | 80/300 M | Causal | 10,000 |
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+ | Semantic to coarse tokens | 80/300 M | Causal | 2x 1,024 |
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+ | Coarse to fine tokens | 80/300 M | Non-causal | 6x 1,024 |
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  ### Release date
 
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  ## Broader Implications
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  We anticipate that this model's text to audio capabilities can be used to improve accessbility tools in a variety of languages.
 
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  While we hope that this release will enable users to express their creativity and build applications that are a force
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  for good, we acknowledge that any text to audio model has the potential for dual use. While it is not straightforward
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+ to voice clone known people with Bark, it can still be used for nefarious purposes. To further reduce the chances of unintended use of Bark,
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  we also release a simple classifier to detect Bark-generated audio with high accuracy (see notebooks section of the main repository).